google/qkeras: papers linking to it

GitHub · 585 stars · 108 forks · Python · license Apache-2.0 · created 2019 · github.com/google/qkeras

← Code and data repositories cited in research papers

Research papers in the 480 tracked journals that link to google/qkeras (https://github.com/google/qkeras), read from their Crossref records: by year, category and journal, the family tree of papers building on one another, and the linked repositories derived from it or that it derives from.

Key findings#

4 papers in the tracked journals link to the GitHub repository google/qkeras in their Crossref records, the first in 2021; most of them (2) in 2021.
By category: AI (4); the journals with the most are Nature Machine Intelligence (3) and Neural Computing and Applications (1).
4 of the papers build on one another: a later paper cites an earlier one that also links google/qkeras.

By year#

20212025

Papers linking to google/qkeras by publication year
Year	Papers
2021	2
2022	1
2025	1

Journals#

Journals whose papers link to google/qkeras most
Journal	Papers
Nature Machine Intelligence	3
Neural Computing and Applications	1

Family tree#

Each paper sits under the earlier paper it builds on; papers that cite no other paper here start a branch of their own.

Automatic heterogeneous quantization of deep neural networks for low-latency inference on the edge for particle detectors Nature Machine Intelligence, 2021
- Resource-efficient inference for particle physics Nature Machine Intelligence, 2021 — cites the paper above
- Autoencoders on field-programmable gate arrays for real-time, unsupervised new physics detection at 40 MHz at the Large Hadron Collider Nature Machine Intelligence, 2022 — cites the paper above
- Hardware implementation of a quantized CNN model for early detection of skin cancer cells using hls4ml tool Neural Computing and Applications, 2025 — cites the paper above

Papers linking to google/qkeras, most cited first
Published	Title	Journal	Authors	Citations	Link
2021-06-21	Automatic heterogeneous quantization of deep neural networks for low-latency inference on the edge for particle detectors	Nature Machine Intelligence	Claudionor N. Coelho, Aki Kuusela, Shan Li et al.	226	cites it
2022-02-23	Autoencoders on field-programmable gate arrays for real-time, unsupervised new physics detection at 40 MHz at the Large Hadron Collider	Nature Machine Intelligence	Ekaterina Govorkova, Ema Puljak, T. K. Aarrestad et al.	79	cites it
2025-07-21	Hardware implementation of a quantized CNN model for early detection of skin cancer cells using hls4ml tool	Neural Computing and Applications	Ehsan Arefi, Morteza Mousazadeh	1	cites it
2021-08-17	Resource-efficient inference for particle physics	Nature Machine Intelligence	David Rousseau	0	cites it

How this is measured#

Links are read from each paper's Crossref record as its publisher deposited it: the URLs and repository DOIs in its reference list (the software and data it cites) and its supplementary links (“is-supplemented-by”: its own code or data). A paper that gives its code only in the text, a footnote or a data availability statement is not counted, and some publishers deposit reference lists without their URLs, so every count here is a lower bound. Repository details come from the GitHub REST API (stars, forks, and the repository a fork was made from), the Hugging Face Hub API (likes, downloads, and the base model a model was derived from) and DataCite (Zenodo and other data DOIs, and the GitHub release a Zenodo record archives), read again every month.

Cite this page

Scholar4AI. (2026). google/qkeras: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/github-google-qkeras

@misc{scholar4ai-code-github-google-qkeras,
  author = {{Scholar4AI}},
  title = {google/qkeras: papers linking to it},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/code/github-google-qkeras}},
  urldate = {2026-11-03},
  note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}

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